Model Comparison

Efficient Sequential Testing with Evidence Ratios

This post is a “blog version” of the vignette of my first R package, which is itself greatly inspired from the first post of this blog.

Why the Akaike Information Criterion is as much 'Bayesian' as the Bayesian Information Criterion

According to Rubin (1984), a Bayesianly justifiable analysis is one that “treats known values as observed values of random variables, treats unknown values as unobserved random variables, and calculates the conditional distribution of unknowns given knowns and model specifications using Bayes’ theorem”